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Flinders University, 21 September, 2010 Academic Workloads.

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Presentation on theme: "Flinders University, 21 September, 2010 Academic Workloads."— Presentation transcript:

1 Flinders University, 21 September, 2010 Academic Workloads

2 Changing nature of academic work Academic staff –Train future professionals –Conduct scholarly and applied research –Build international linkages –Collaborate with business –Generate export revenue –Create new knowledge based export products –Mentor individuals –Contribute to the create life of the broader community –Run large complex organisations –Train their own future workforce

3 Changing nature of academic work Hamish Coates and Leo Goedegebuure in “The real academic revolution” argue that the role consists of 5 main domains –Scholarship of discovery –Scholarship of teaching –Scholarship of Integration –Scholarship of application –Leadership and management

4 Changing nature of academic work Coates and Goedegebuure suggest that –Academic work should be reconceptualised –Career profiles should be more flexible –Institutions should find ways of ensuring academics get a broad range of experience across a career –Improve measures of performance –Improve RHd training to facilitate an academic career –Universities engage more in capacity building

5 Issues from a professional HR perspective Academic reward structure –Modelled on the concept of a generalist academic career –Usually contains clearly measurable standards for research –Measures for teaching excellence are more contestable –Service /Leadership standards tend to be weaker Academic Workloads models –Hard wired measure is teaching contact hours (input) –Research “undirected” hard to measure in hours

6 What’s driving workload models? UK –Long a feature of pre 1992 institutions –Linkage with Transparent Approach to Costing Australia –Driven by perceptions of academic overwork –Multiple surveys of workloads of academic profession –Industrial response as a means of imposing a staff centred solution. US –Seen as good practice –General agreement on appropriate face to face teaching obligations New Zealand –Practice varies –More recent industrial issue

7 What’s driving the push for workload models in Australia Surveys of academic staff satisfaction ( 1990 – 1999) –Progressive decline in job satisfaction –Concerns about workloads –Progressive increase in the number of hours worked Occupational Stress in Australian Universities 2002 (Winefield et al) –Highly stressed profession –Mitigation strategies Fair procedures Job security Trust in management Changes in academic work, 2002 ( Anderson et al) –Pressure to perform –Lack of control over task and breadth of task –Workloads –Satisfaction less in less well funded institutions

8 The industrial response Addition of workloads management clauses in EBAs EBAs negotiated at local level, so clauses reflect some local issues Unlike other industrialised occupations, academic staff had no regulated set hours of work (national maximum 38 hrs per week). Study of progressive changes in workloads management clauses in 5 universities Progressively more complex and more prescriptive between 1997 - 2011

9 What the workload clauses have in common Definition of what constitutes academic work –Teaching, research and service –Definitions have progressively become more detailed Framework approach Workload models determined at departmental/school level References to OHS, work life balance Grievance or review process

10 Australian collective agreements Become progressively more prescriptive By 2011 mandate –Nomination of upper limit of hours ( 1800, 1725 hours per annum, or average 36 or 37.5 hours per week) –Specific limits on teaching time, or time splits between teaching research and administration specified (40:40:20) –Models to take into account both task, and size of task, e.g. class sizes, modes of delivery, overseas delivery etc. –Locally determined models to be transparent, written, agreed by staff member, published to all –More prescriptive maxima clauses, e.g. no teaching after 9.00pm Grievances handled through standard grievance process

11 2009 – 2011 Linkage between WAM and performance expectations Workload associated with contribution to work group’s performance plan Performance reviews and promotion take into account annual work plan Allocation based on outputs, rather than inputs Increasingly specific requirements for attendance Work must be undertaken in line with University strategy

12 The US Workload management is a significant issue Acceptance of a standard load of 12 hours undergraduate teaching or 9 post graduate Some have provision for overtime ( teaching greater than load) Most university policies seek to balance work between teaching, research and service by a formula based on hours or % Some university policies recognise link between work allocation, performance evaluation and reward Many States have prescribed minimum contact hours for academic staff.

13 UK: MAW report recommends Having a university policy which is highly flexible Most issues determined at the local level –Measures Hours ( inputs) or Units ( outputs) Specified maxima, or median times –What work is included and to what level of detail –How are under and over workloads to be managed –Time frames for review –Linkage with wider faculty /university processes Consultation over all aspects, including meaning of transparency Implementation on a university wide basis over an extended time frame

14 New Zealand Problem solving academic workloads management; a university response (Paewei, Mayer, Houston) ( Massey University) Implementation of workloads models as solution to an industrial dispute after major staff reductions Broad framework – Departmental development of models, review of 6 models Lessons learnt –Breadth and complexity of academic work –Workload models only one way to solve the workload issue –Academic units absorbed extra work, rather than looking at alternate strategies for management –Importance of developing a template and defining at University level what an acceptable workload is –Linear solutions are not always effective in a complex organisation –Where worked well units had been collegial and interactive, paid attention to transparency, recognised the impact of the local environment

15 Have academic workload models achieve the desired aim? Attractiveness of the Australian academic profession ( Coates et al) –Progressive increase in average hours worked –1999 (49.3 pw) – 2007 ( 50.6 pw) Impacts of different types of WAMs on academic job satisfaction and working life ( Vardi) –Three different WAMs in one institution Contact hours Actual hours worked Points model –WAMs deal with work allocation not workload management –Better acceptance of all models by Heads than departmental staff –Most accepted was “contact hours” model. –More complex models not seen as attractive and resulted in more petty disputes

16 Issues with workload models WLM not a resource allocation model WLM models are inherently conservative, assume an accretion rather than a reorganisation of work Impact of new media and forms of communication on traditional workload Difficulty of achieving internal consistency in application Some models only measure teaching inputs and assume research is done in residual time Difficulty of measuring research allocation Implicit links with promotion opportunities What are the appropriate equivalances eg face to face teaching and supervision WAMs permit comparisons giving rise to claims that WAM is flawed Disputes around the model

17 Comments Workload models are a part of university life All systems will have problems as they cater for individuals and high levels of complexity Consultation on implementation important Importance of flexibility to take account of individual circumstances In universities, management processes are effective if perceived as “meaningful” and “fair” by those involved Increasingly workload management processes are linked to other university processes which are also “meaningful” to staff Universities will commence adapting workload models to budgets, performance management and promotion

18 Different approaches to workload model implementation

19 Director, Workloads Management. “There is a long way to go with something that is conceptually so simple”

20 Approaches to implementation Different approaches to model development –Hours –% of time –Weighted hours or points –No or limited measures ( allocation of tasks) Whole of University approach –Single system for whole University –Local flexibilities built in, but standard weighting factors –Often developed when maxima are prescribed in agreements. Framework approach –University develops generic standards, and Faculties/Schools implement as they think fit.

21 University wide implementation Collective agreement –Distinguished between Allocated work ( teaching, work associated with teaching, administration of research) Unallocated work ( research, scholarship, professional development –Maximum hours ( 1645 pa. Annual hours excluding holidays) –Required workloads to be equalised –40% ( teaching), 40% ( research), 20% ( service ) split as a guide –Required Faculty based workload development

22 University wide implementation Created a steering group ( including Union members) With external consultant assistance, developed a workload model Tested the model by requiring all staff to complete the model using actual hours worked Test revealed large differences in workload, with Assoc Profs and Profs carrying the highest workload

23 University wide model Result of actual hours survey

24 University wide implementation Activity bands developed –Teaching 20% – 70% –Research 10 % - 60% –Service and Professional activity 20% Weightings for teaching and associated duties built into system No weightings or means of accounting for research ( to be developed) All staff guaranteed 20% service, professional activity allocation Seen as an annual allocation process, monitoring done through performance development process System being trialled in one faculty and a variety of schools

25 Faculty/School models - Basic Establishment of an expected staff work profile –Courses taught –Thesis supervision and marking –Research ( submission of articles, grant applications) –Administration Work allocated by reference of what is required to be done, staff member’s career and professional circumstances Works well if –Course offerings are static –Staff well established –Staff numbers and course offerings are small and located on one campus Problems –Size of staff –Multi campus institutions –Different modes of delivery

26 Faculty/Model - Hours Establish an annual contact hours requirement for teaching, research and administration to total the annual required hours Each activity is given a time allocation, eg. lecture 2 hours, marking papers 36min In some cases hourly allocation x no of students Workload is calculated by taking components and building up the annual required contact hours In some cases workloads are lowered for early career academics Most models prioritise meeting the teaching and service hours, with the balance of the allocation for research

27 Faculty model - Hours Advantages –Simple –Easy to manage and monitor –Staff are clear about the general duties Disadvantages –Does not nuance for large classes, different forms of delivery –Research time allocation is based on inputs ( i.e. hours) rather than productivity

28 Faculty model - Points Annual hours established for teaching, research, service converted to total points required Base hourly time allocation established for teaching and service, eg for face to face lecture Hourly rates multiplied by factors reflecting level of complexity, size of class, nature of delivery etc to generate a points score Points allocated for service, professional development etc. Research points developed based on –Previous outputs as measured –Projected activity

29 Faculty model - Points Disadvantages –Very complex –Involves consideration of past performance –Time consuming Advantages –More nuanced, takes account of class size, marking etc –Teaching allocations may be perceived as being more fair –Does measure research and research time

30 Faculty model – Percentages Percentages of time to be allocated to each class of work adopted, eg 40/40/20 Some models identify fixed percentages of time to be allocated to a particular activity Sliding scale of acceptable percentage of time allocation to each major area of work developed, sometimes by level Time allocated by Head of School after consideration of –Tasks to be done –Strengths/ interests of the staff member –Expectations of the level of appointment

31 Faculty model - Percentages T and R Academ ic% Teachin g RHD supervi sion Researc h ServiceProfessi onal Develop ment External Engage ment Total Asst Lecturer 30% – 50% nil30% - 60% nil10% – 15% nil100% Lecturer 30% – 60% 0% -5%30% - 60% 0% - 5% 0% - 10% 0 – 5%100% Snr Lecturer 30% - 60% 5% - 10% 30% - 60% 5% - 10% 5%0% - 5% 100% Assoc Prof 20% - 60% 10% - 15% 40% - 60% 5% - 20% 5%0% - 10% 100% Prof. 10% - 50% 10% - 15% 40% - 60% 10% – 20% 5%0%- 10% 100%

32 Faculty model - Percentages Advantages –More flexible –Able to be tailored to specific career levels and individual aspirations –Does not involve complex calculations Disadvantages –Could be perceived as unfair as allocations are more fluid –Harder to demonstrate “equity”

33 Implementation issues

34 Issues Lack of consistency in data collection and approach Core data re courses and programs may be poor Effort in maintaining data Ambiguity gives rise to potential –Perceptions of managerial manipulation –Flexibility in work allocation

35 People issues Equity –Most aim for parity not equity Transparency –Practices differ as to who can see what Different attitudes to work and career stages Leadership capacity/experience of Head of School Workload models surface existing problems Gaming?

36 Metrics and weightings - teaching Hours allocation varies markedly Comparisons difficult across countries Sample comparison hours per week ActivityAustraliaUKNZ F2F hour lecture 2 - 32.3 – 3.231.25xn - 4 RHD supervision per student 1.1 – 3.751.08 - 3 Course coordination 9.4 xn0.2 – 1.171.7 – 3.5

37 Teaching metrics DomainActivityWeightingAllocationEnrolmentHours multiplier ServiceNew staffAllocation6000 ServiceTraining / Developme nt Allocation3000 ServiceProg. Coordinati on Allocationx number 320.10 Manageme nt HODAllocation103500 Supervisio n PhDNo hours0750 TeachingWorkshopNo hours001.5 TeachingLectureNo hours003

38 Metrics and weightings - research Research counted in some Australian and New Zealand systems Allocations determined by –Prior measured research performance over a nominated period of years, and –Supervision of RHD students, and –Projected research plan for forthcoming year including projected outputs

39 Links to performance Workload allocation models have implicit or explicit links to –Performance appraisal –Promotion Normal approach is work allocation is managed through the WAM, and performance issues through appraisal. RMIT ( and others) has integrated work plans based on workload allocation, performance appraisal and incremental advancement

40 Decisions re implementation University wide approach, local approach or hybrid USQ has a hybrid approach, with a University wide data base which allows for local differences in weightings Access - who can see individual workload allocations Equity or parity ? Controls ( double dipping) Use for broader purposes, eg resource allocation, resource requests

41 Future trends Complexity of WAMs finely nuanced to equity will mean that they become less relevant WAM will become the basis for assessment for performance appraisal WAMs will become more finely nuanced to individual careers and career aspirations WAMS may become part of the university’s employee value proposition May be an industrial ‘backlash’ against WAMs


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